Analyse Rapide des notes - DS1¶
import pandas as pd
from ipywidgets import interact, interactive, fixed, interact_manual, IntSlider
# Standard plotly imports
import chart_studio.plotly as py
import plotly.graph_objs as go
from plotly.offline import iplot, init_notebook_mode
# Using plotly + cufflinks in offline mode
import cufflinks as cf
cf.go_offline(connected=False)
init_notebook_mode(connected=False)
Continus - DSC1¶
df=pd.read_csv("Notes_DSC1.csv", encoding="latin-1")
df.describe()
| Note | Exo1 | Exo2 | Exo 3 | |
|---|---|---|---|---|
| count | 28.000000 | 28.000000 | 28.000000 | 28.000000 |
| mean | 12.660714 | 3.401786 | 4.026786 | 5.000000 |
| std | 3.609539 | 1.198648 | 1.774745 | 1.635826 |
| min | 4.500000 | 0.750000 | 0.500000 | 0.750000 |
| 25% | 10.625000 | 3.000000 | 2.937500 | 4.437500 |
| 50% | 13.000000 | 3.875000 | 4.250000 | 5.500000 |
| 75% | 15.250000 | 4.250000 | 5.062500 | 6.062500 |
| max | 18.250000 | 4.750000 | 7.250000 | 7.000000 |
df['Note']=df["Note"]*100/20
df['Exo1'] = df['Exo1']*100/5
df['Exo2'] = df['Exo2']*100/8
df['Exo 3'] = df['Exo 3']*100/7
df["Note"].iplot(kind="histogram", bins=20, theme="white", title="Répartition des notes",xTitle='Notes sur 100', yTitle='Quantité')
df["Exo1"].iplot(kind="histogram", bins=20, theme="white", title="Répartition des notes - Exercice 1 - Calculs matriciel",xTitle='Notes sur 100', yTitle='Quantité')
df["Exo2"].iplot(kind="histogram", bins=20, theme="white", title="Répartition des notes - Exo 2 - Géométrie",xTitle='Notes sur 100', yTitle='Quantité')
df["Exo 3"].iplot(kind="histogram", bins=20, theme="white", title="Répartition des notes - Exo 3 - Matrices, inversion",xTitle='Notes sur 100', yTitle='Quantité')
Alternants - DSA1¶
df=pd.read_csv("Notes_DSA1.csv", encoding="latin-1")
df.describe()
| Note | Exo1 | Exo2 | Exo 3 | |
|---|---|---|---|---|
| count | 22.000000 | 22.000000 | 22.000000 | 22.000000 |
| mean | 11.681818 | 2.579545 | 3.625000 | 5.340909 |
| std | 3.132189 | 0.853516 | 1.873611 | 1.493130 |
| min | 6.000000 | 1.000000 | 0.000000 | 1.500000 |
| 25% | 9.562500 | 2.125000 | 2.437500 | 4.312500 |
| 50% | 11.750000 | 2.500000 | 3.750000 | 5.500000 |
| 75% | 13.187500 | 3.187500 | 4.437500 | 6.500000 |
| max | 19.000000 | 4.000000 | 8.000000 | 7.000000 |
df['Note']=df["Note"]*100/20
df['Exo1'] = df['Exo1']*100/5
df['Exo2'] = df['Exo2']*100/8
df['Exo 3'] = df['Exo 3']*100/7
df["Note"].iplot(kind="histogram", bins=20, theme="white", title="Répartition des notes",xTitle='Notes sur 100', yTitle='Quantité')
df["Exo1"].iplot(kind="histogram", bins=20, theme="white", title="Répartition des notes - Exercice 1 - Calculs matriciel",xTitle='Notes sur 100', yTitle='Quantité')
df["Exo2"].iplot(kind="histogram", bins=20, theme="white", title="Répartition des notes - Exo 2 - Géométrie",xTitle='Notes sur 100', yTitle='Quantité')
df["Exo 3"].iplot(kind="histogram", bins=20, theme="white", title="Répartition des notes - Exo 3 - Matrices, inversion",xTitle='Notes sur 100', yTitle='Quantité')